AI RESEARCH
Capturing Multivariate Dependencies of EV Charging Events: From Parametric Copulas to Neural Density Estimation
arXiv CS.LG
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ArXi:2603.29554v1 Announce Type: new Accurate event-based modeling of electric vehicle (EV) charging is essential for grid reliability and smart-charging design. While traditional statistical methods capture marginal distributions, they often fail to model the complex, non-linear dependencies between charging variables, specifically arrival times, durations, and energy demand. This paper addresses this gap by